James Chase
Senior Machine Learning Engineer
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Machine Learning Engineer
London | Hybrid | Permanent
We're working with a leading global financial services organisation that is making a significant investment in AI and Machine Learning, building new AI Innovation teams to develop and deploy next-generation AI solutions.
This is an opportunity for an experienced Machine Learning Engineer to play a key technical role in designing and building greenfield AI/ML platforms, including sophisticated agentic AI systems, LLM-powered applications and intelligent automation.
We're looking for someone with a strong background in production ML engineering, rather than a predominantly research or Data Science background. You'll need to be comfortable taking complex AI solutions from initial concept and experimentation through to scalable, enterprise-grade production systems.
This is a senior, hands-on individual contributor position, with responsibility for technical architecture, engineering standards and mentoring other engineers, but no direct line management.
The Role
- Architect and develop production-grade ML/AI systems, including GenAI platforms, LLM applications and agentic workflows.
- Design and implement RAG architectures, multi-agent systems and intelligent automation solutions.
- Lead technical decisions around ML architecture, frameworks, model deployment and infrastructure.
- Develop and deploy ML models using Python, PyTorch and modern ML frameworks.
- Build scalable APIs, MLOps pipelines and cloud-native infrastructure to support production AI systems.
- Take AI concepts and proofs of concept through to reliable, scalable production solutions.
- Establish engineering best practices around testing, CI/CD, model monitoring, performance and AI governance.
- Provide technical guidance and mentorship while remaining actively involved in hands-on engineering.
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What We're Looking For
- 12+ years' professional experience building production AI/ML systems, with a strong software engineering foundation.
- Extensive hands-on Python experience and strong knowledge of ML algorithms, deep learning and frameworks such as PyTorch.
- Proven experience architecting and delivering scalable ML platforms and solutions from the ground up.
- Advanced practical experience with Generative AI, LLMs, RAG, agentic AI and multi-agent systems.
- Experience with model training, fine-tuning, evaluation and production deployment.
- Strong MLOps knowledge, including Docker, Kubernetes, CI/CD, model monitoring and workflow orchestration.
- Experience with AWS or Azure, along with API development using frameworks such as FastAPI.
- Ability to make and justify complex architectural decisions, including technology selection and engineering trade-offs.
- Experience mentoring engineers and providing technical leadership without necessarily managing a team.
- A degree in Computer Science, Machine Learning, Data Science, Applied Mathematics or a related discipline.
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Why Consider It?
- This is an opportunity to join a well-funded AI transformation programme with significant executive backing, where you'll have genuine influence over technical direction and the opportunity to build new ML capabilities rather than simply maintain existing systems.
- You'll be working on challenging problems involving NLP, document intelligence, reasoning systems and intelligent automation, with access to modern AI infrastructure and the opportunity to influence how AI is adopted across a global organisation.
- If you're an experienced, hands-on ML Engineer who enjoys designing complex systems, solving difficult engineering problems and turning emerging AI technologies into real production solutions, I'd be interested in speaking with you.
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